“Your AI is impressive, but my code does not have any bugs” managing false positives in industrial contexts
Szymon Stradowski, Lech Madeyski · Science of Computer Programming · 2025
Context “Your AI is impressive, but my code does not contain any bugs”— such a statement from a software developer is the antithesis of a quality mindset and open communication. What makes it worse is that it is oftentimes true. Objective This paper analyses false positives' impact and related challenges in machine learning software defect prediction and describes the mitigation possibilities. Methods We propose a broad-picture perspective on dealing with false positive predictions based on what we learned from our industrial implementation study in Nokia 5G. Results Accordingly, we draw a new direction in transitioning defect prediction into a well-established industry practice, as well as highlight potential emerging topics in predictive software engineering. Conclusion Increasing human buy-in and the business impact of predictions significantly improves the chances of future software defect prediction industry adoptions to succeed.